Discussion of "Neural network modeling of resilient modulus using routine subgrade soil properties" by Musharraf Zaman, Pranshoo Solanki, Ali Ebrahimi, and Luther White

The authors presented a good comparison of different artificial neural network (ANN) models to predict the resilient modulus of subgrade (MR) using routine subgrade soil properties, which include grain size distribution, plasticity index, compaction characteristics, and unconfined compressive strength of soil. The database is limited to soils from the state of Oklahoma. The novelty of the paper lies in presentation of the input and output data in terms of its frequency distribution both for training and testing data. Unlike previous studies, the data were not normalized and, hence, it would have been better to see the distribution of the normalized data, followed by the necessary model development